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Faiss download for Linux

Free download Faiss Linux app to run online in Ubuntu online, Fedora online or Debian online

This is the Linux app named Faiss whose latest release can be downloaded as v1.7.3.zip. It can be run online in the free hosting provider OnWorks for workstations.

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Faiss


DESCRIPTION

Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. Vectors that are similar to a query vector are those that have the lowest L2 distance or the highest dot product with the query vector. It also supports cosine similarity, since this is a dot product on normalized vectors.



Features

  • The library is mostly implemented in C++, with optional GPU support provided via CUDA, and an optional Python interface
  • Faiss handles collections of vectors of a fixed dimensionality d, typically a few 10s to 100s
  • The CPU version requires a BLAS library. It compiles with a Makefile and can be packaged in a docker image
  • Faiss is built around an index type that stores a set of vectors, and provides a function to search in them with L2 and/or dot product vector comparison
  • The optional GPU implementation provides what is likely the fastest exact and approximate nearest neighbor search implementation for high-dimensional vectors
  • Faiss is built around the Index object. It encapsulates the set of database vectors, and optionally preprocesses them to make searching efficient


Programming Language

C++


Categories

Clustering, Libraries

This is an application that can also be fetched from https://sourceforge.net/projects/faiss.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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